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SITEKNIK: Sistem Informasi, Teknik dan Teknologi Terapan
Published by RAM PUBLISHER
ISSN : 30901626     EISSN : 30323991     DOI : -
Core Subject : Humanities, Science, Engineering,
Humanities Automotive Engineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Decision Sciences, Operations Research & Management
SITEKNIK: Sistem Informasi, Teknik dan Teknologi Terapan or in English the publication title Information Systems, Engineering and Applied Technology is an open access journal committed to publishing high quality research articles in the fields of Information Systems, Informatics, Digital Communication Information Technology, Tourism Technology, Transportation Technology, Agricultural Technology, Plantations, Fisheries, Marine, Environmental Technology, Artificial Intelligence, Mechanical Engineering, Electrical Engineering, Industrial Engineering and Civil Engineering. Published 4 X (Times) a year in January, April, July, and October. SITEKNIK accepts and selects quality articles and focuses on providing the best service for writers. SITEKNIK is committed to being a leading platform for researchers to share their innovative findings. We also provide a fast and transparent review process to ensure the quality and originality of each published article.
Arjuna Subject : Ilmu Komputer (semua kategori) - Sistem Informasi
Articles 5 Documents
 1 
Search results for , issue "Vol. 3 No. 1 (2026): January" : 5 Documents clear
Rancangan Arsitektur Sistem Analisis Sentimen Kinerja POLRI Berbasis Cloud PaaS dan IndoBERT Novantri Prasetya Putra
SITEKNIK: Sistem Informasi, Teknik dan Teknologi Terapan Vol. 3 No. 1 (2026): January
Publisher : RAM PUBLISHER

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5281/zenodo.18366548

Abstract

Pada era ini, kepercayaan publik terhadap institusi penegak hukum seperti POLRI sangat dipengaruhi oleh opini yang berkembang di media sosial. Namun, analisis terhadap data masif (Big Data) ini menghadapi dua tantangan utama yaitu keterbatasan metode klasik dalam memahami konteks bahasa Indonesia (seperti sarkasme dan bahasa gaul) serta tingginya kebutuhan sumber daya komputasi untuk menjalankan model Deep Learning. Penelitian ini bertujuan untuk merancang sebuah kerangka kerja sistem analisis sentimen terintegrasi yang tidak hanya akurat, tetapi juga efisien secara infrastruktur dan strategis dalam pengambilan keputusan. Metodologi penelitian ini menggabungkan model IndoBERT untuk klasifikasi teks kontekstual, metode Analytic Hierarchy Process (AHP) untuk pembobotan prioritas kinerja, dan arsitektur Cloud Platform as a Service (PaaS) sebagai lingkungan implementasi. Hasil penelitian ini berupa rancangan arsitektur sistem yang memanfaatkan layanan serverless dan GPU berbasis cloud untuk efisiensi biaya dan skalabilitas otomatis. Simulasi sistem menunjukkan bahwa integrasi IndoBERT mampu mendeteksi sentimen negatif terselubung, sementara AHP berhasil mentransformasi data sentimen menjadi daftar prioritas perbaikan yang dapat ditindaklanjuti (actionable insights). Penelitian ini menyimpulkan bahwa adopsi arsitektur berbasis Cloud PaaS adalah solusi paling layak (feasible) untuk mengimplementasikan model NLP mutakhir di lingkungan pemerintahan tanpa investasi perangkat keras yang masif.
Perancangan Enterprise Architecture Pada UPT Perpustakaan Pondok Pesantren Salafiyah Syafi’iyah Sukorejo Situbondo Berbasis TOGAF ADM Akhlis Munazilin; Arif Ferdiansyah; Bagus Maulana Zulkarnain
SITEKNIK: Sistem Informasi, Teknik dan Teknologi Terapan Vol. 3 No. 1 (2026): January
Publisher : RAM PUBLISHER

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5281/zenodo.18334065

Abstract

UPT Perpustakaan Pondok Pesantren Salafiyah Syafi’iyah Sukorejo merupakan pusat literasi yang berperan penting dalam mendukung kegiatan pendidikan santri dan masyarakat. Namun, proses pelayanan, integrasi data, dan pengelolaan sistem informasi masih menghadapi beberapa kendala, seperti pencatatan manual yang tersisa, hilangnya kartu santri, keterbatasan waktu layanan, serta persoalan teknis jaringan. Penelitian ini bertujuan merancang Enterprise Architecture menggunakan kerangka kerja TOGAF ADM sebagai panduan pengembangan sistem informasi perpustakaan. Hasil penelitian berupa model arsitektur bisnis, data, aplikasi, dan teknologi yang dapat dijadikan blueprint pengembangan sistem informasi terpadu guna meningkatkan efisiensi layanan dan mendukung proses digitalisasi perpustakaan.
Analisis Strategis Dampak Transformasi Digital Indonesia: Studi Literatur pada Sektor Publik, Ekonomi, dan Pendidikan Dewi Setiowati; Diah Indriani; Inayah Wisartika; Selvi Alvinda Fitriyani
SITEKNIK: Sistem Informasi, Teknik dan Teknologi Terapan Vol. 3 No. 1 (2026): January
Publisher : RAM PUBLISHER

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5281/zenodo.18395894

Abstract

Transformasi digital merupakan instrumen strategis untuk meningkatkan efisiensi operasional dan kualitas pelayanan di berbagai sektor. Namun, implementasinya di Indonesia masih menunjukkan hasil yang beragam dan ketimpangan dampak antar wilayah. Penelitian ini menggunakan metode Systematic Literature Review (SLR) terhadap 20 jurnal ilmiah bertema transformasi digital di Indonesia pada sektor publik, UMKM, dan pendidikan dalam rentang tahun 2020–2025. Data dianalisis secara kualitatif melalui teknik analisis tematik untuk memetakan pola keberhasilan dan hambatan sistemik. Hasil penelitian menunjukkan bahwa transformasi digital di Indonesia masih didominasi oleh perubahan administratif (digitization) dan belum sepenuhnya mencapai transformasi substansial. Keberhasilan transformasi bergantung pada variabel multiplikatif antara kepemimpinan digital dan kesiapan operasional SDM. Adanya kesenjangan digital (digital divide) yang signifikan, di mana wilayah metropolitan (Jabodetabek) mendapatkan dampak ekonomi positif yang nyata, sementara wilayah daerah (Pariaman dan Bima) masih menghadapi hambatan literasi dan infrastruktur. Hambatan utama yang teridentifikasi fragmentasi data (silo data), rendahnya kompetensi digital, dan isu keamanan siber. 
A Systematic Literature Review on AI Architecture Frameworkfor Product Analysis & Recommendation System in Electronic Service Ahmadi, Irfan Fahmi
SITEKNIK: Sistem Informasi, Teknik dan Teknologi Terapan Vol. 3 No. 1 (2026): January
Publisher : RAM PUBLISHER

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5281/zenodo.18431166

Abstract

The rapid growth of electronic services has created significant opportunities for personalized product recommendations through artificial intelligence (AI) systems. However, existing recommendation algorithms face critical challenges, including scalability, cold-start issues, and performance degradation in big data environments. This research performs a systematic review of 73 studies published from 2022 until 2024 to examine AI architecture frameworks applied to product analysis and recommendation systems in electronic service. The review identifies dominant frameworks such as CNN, RNN/LSTM, TensorFlow, Spark, and emerging technologies like GNN, alongside distributed infrastructures such as Hadoop for large-scale data processing. Research methods observed include experiments, benchmarks, simulations, surveys, and case studies. Key findings emphasize performance and efficiency improvements, accuracy, and scalability concerns. Based on these insights, this paper proposes a multi-layered AI architecture framework integrating data ingestion, distributed storage, model development, MLOps orchestration, privacy-preserving learning, and adaptive feedback loops. The proposed framework addresses scalability and sustainability challenges while ensuring high-performance recommendation capabilities. This study contributes a comprehensive blueprint for organizations seeking to deploy robust, scalable, and privacy-aware AI systems in dynamic e-service environments.
ARTIFICIAL INTELLIGENCE ADOPTION AND IMPLEMENTATION IN INDONESIA: POLICY FRAMEWORKS, SECTORAL APPLICATIONS, AND FUTURE PROSPECTS Saskiya Farannisa
SITEKNIK: Sistem Informasi, Teknik dan Teknologi Terapan Vol. 3 No. 1 (2026): January
Publisher : RAM PUBLISHER

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5281/zenodo.18431719

Abstract

Indonesia stands at a pivotal moment in its digital transformation journey, with Artificial Intelligence (AI) emerging as a strategic catalyst for economic growth and social development. This paper presents a comprehensive analysis of AI adoption and implementation in Indonesia, examining the national policy framework, sectoral applications, technological infrastructure, and institutional mechanisms established to accelerate AI development. The research reveals that Indonesia's National AI Strategy (Stranas KA) 2020-2045, complemented by institutional structures such as the AI Innovation Center (PIKA) and the Artificial Intelligence Industry Research and Innovation Collaboration (KORIKA), has created a comprehensive ecosystem for AI advancement. Current implementations span critical sectors including healthcare, agriculture, finance, manufacturing, and government services. However, significant challenges persist, particularly in digital infrastructure development, cybersecurity readiness, talent acquisition and retention, and ethical AI governance. Analysis of 43 recent studies from accredited journals indicates that quantitative research methodologies dominate AI investigations in Indonesia, with healthcare and education emerging as primary research foci. This paper concludes that while Indonesia possesses considerable potential to leverage AI for competitive advantage—with projected economic contributions reaching USD 366 billion over the next decade—successful realization requires sustained investment in infrastructure, comprehensive talent development programs, robust ethical frameworks, and enhanced cross-sector collaboration. The findings underscore the necessity of bridging the gap between policy formulation and operational implementation to ensure Indonesia emerges as a regional AI leader in Southeast Asia.

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